Articles from July 2022

How to Turn Seawater to Drinking Water With the Push of a Button

MIT researchers have developed a portable desalination unit, weighing less than 10 kilograms, that can remove particles and salts to generate drinking water. The suitcase-sized device, which requires less power to operate than a cell phone charger, can also be driven by a small, portable solar panel, which can be purchased online for around $50. It automatically generates drinking water that exceeds World Health Organization quality standards. The technology is packaged into a user-friendly device that runs with the push of one button. Unlike other portable desalination units that require water to pass through filters, this device utilizes electrical power to remove particles from drinking water. Eliminating the need for replacement filters greatly reduces the long-term maintenance requirements. This could enable the unit to be deployed in remote and severely resource-limited areas, such as communities on small islands or aboard seafaring cargo ships. It could also be used to aid refugees fleeing natural disasters or by soldiers carrying out long-term military operations.

This is really the culmination of a 10-year journey that I and my group have been on. We worked for years on the physics behind individual desalination processes, but pushing all those advances into a box, building a system, and demonstrating it in the ocean, that was a really meaningful and rewarding experience for me,” says senior author Jongyoon Han, a professor of electrical engineering and computer science, and a member of the Research Laboratory of Electronics (RLE).

Joining Han on the paper are first author Junghyo Yoon, a research scientist in RLE; Hyukjin J. Kwon, a former postdoc; SungKu Kang, a postdoc at Northeastern University; and Eric Brack of the U.S. Army Combat Capabilities Development Command (DEVCOM). The research has been published online in Environmental Science and Technology.


Toyota plans to roll out hydrogen fuel-cell trucks for the Japanese market next year

Automotive giant Toyota, along with three other partners, will work on the development of light-duty fuel cell electric trucks with a view to rolling them out in Japan next year. In a statement Tuesday, Toyota said it would collaborate with  Isuzu, Hino Motors and Commercial Japan Partnership Technologies Corporation (CJPT) on the project. Both Isuzu and Hino carried the same statement as Toyota on their respective websites. One potential use case for the fuel cell vehicles could be in the supermarket and convenience store sector, where Toyota said light-duty trucks were “required to drive long distances over extended hours to perform multiple delivery operations in one day.

The company also listed fast refueling as a requirement for vehicles operating in this segment.

The use of FC [fuel cell] technology, which runs on high energy density hydrogen and has zero CO2 emissions while driving, is considered effective under such operating conditions,” it added.

According to the company, an introduction to the market is slated for after January 2023, with light duty fuel-cell trucks used at distribution sites in Fukushima Prefecture and other projects in Tokyo. Hino Motors is part of the Toyota Group, while CJPT was established by Isuzu, Toyota and Hino in 2021. Toyota started working on the development of fuel-cell vehicles — where hydrogen from a tank mixes with oxygen, producing electricity — back in 1992. In 2014, it launched the Mirai, a hydrogen fuel cell sedan. The business says its fuel cell vehicles emit “nothing but water from the tailpipe.”

Alongside the Mirai, Toyota has had a hand in the development of larger hydrogen fuel cell vehicles. These include a bus called the Sora and prototypes of heavy-duty trucks. Alongside fuel cells, Toyota is looking at using hydrogen in internal combustion engines.


Roboticists Discover alternative Physics

Energy, mass, velocity. These three variables make up Einstein‘s iconic equation E=MC2. But how did Einstein know about these concepts in the first place? A precursor step to understanding physics is identifying relevant variables. Without the concept of energy, mass, and velocity, not even Einstein could discover relativity. But can such variables be discovered automatically? Doing so could greatly accelerate scientific discovery. This is the question that researchers at Columbia Engineering posed to a new AI program. The program was designed to observe  through a , then try to search for the minimal set of fundamental variables that fully describe the observed dynamics. The study was published on July 25 in Nature Computational Science. The researchers began by feeding the system raw video footage of phenomena for which they already knew the answer. For example, they fed a video of a swinging double pendulum known to have exactly four “state variables”—the angle and of each of the two arms. After a few hours of analysis, the AI produced the answer: 4.7.

We thought this answer was close enough,” said Hod Lipson, director of the Creative Machines Lab in the Department of Mechanical Engineering, where the work was primarily done. “Especially since all the AI had access to was raw video footage, without any knowledge of physics or geometry. But we wanted to know what the variables actually were, not just their number.”

The researchers then proceeded to visualize the actual variables that the program identified. Extracting the variables themselves was not easy, since the program cannot describe them in any intuitive way that would be understandable to humans. After some probing, it appeared that two of the variables the program chose loosely corresponded to the angles of the arms, but the other two remain a mystery.

We tried correlating the other variables with anything and everything we could think of: angular and linear velocities, kinetic and , and various combinations of known quantities,” explained Boyuan Chen Ph.D., now an assistant professor at Duke University, who led the work. “But nothing seemed to match perfectly.” The team was confident that the AI had found a valid set of four variables, since it was making good predictions, “but we don’t yet understand the mathematical language it is speaking,” he explained.


How to Write Words in the Air

Scientists at Hongtuo Joint Laboratory in Wuhan, China, have invented what sounds like a mysterious yet fascinating laser pen that can write in mid-air — an intriguing approach that could, theoretically, be an onramp to “Star Wars”-esque hologram technology.

The South China Morning Post (SCMP) reported yesterday that the pen uses ultra-short laser pulses to strip the electrons from air particles and turn them into light-emitting plasma with sufficient precision to form words in mid-air.

With the brand new device, we can draw in the air without using paper and ink,” lab lead scientist Cao Xiangdong told the state-affiliated Science and Technology Daily this week, as reported by the SCMP.

The SCMP reported that the scientists said they used 3D scanning to arrange pixels and form Chinese characters, but didn’t completely explain how the process works. Long story short, it sounds awesome, but we’re gonna want to see more in the way of a demo.

The pen reportedly works in incredibly short laser bursts, equivalent to just a few quadrillionths of a second. At the same time, its power output is nearly incomprehensible.

The laser pen can reach one million megawatts, according to the SCMP, which isn’t too far off from the total amount of power the United States can generate. However, because the bursts are so short, the device doesn’t draw an immense amount of power, making it — the scientists say — relatively safe to use.

The team is hoping the pen could someday be used in quantum computing, brain imaging and other advanced tech. Or maybe we’ll even see some awesome new holographic technology.


How to Command a Computer Just by Thinking

The first brain-computer interface device was implanted in a patient in the US earlier in July by a doctor at the medical center, Mount Sinai West, in New York, in an investigatory trial of the startup Synchron’s procedure to help patients suffering from ALS (amyotrophic lateral sclerosis) text by thinking. The procedure involved the doctor threading a 1.5-inch-long implant comprised of wires and electrodes into a blood vessel in the brain of a patient with ALS. The hope is that the patient, who’s lost the ability to move and speak, will be able to surf the web and communicate via email and text simply by thinking, and the device will translate the patient’s thoughts into commands sent to a computerSynchron, the startup behind the technology, has already implanted its devices in four patients in Australia, who haven’t experienced side effects and have been able to carry out such tasks as sending WhatsApp messages and making online purchases.

The implant was a major step forward in a nascent industry, putting the Brooklyn-based company ahead of competitors, including ahead of Elon Musk’s Neuralink Corp.

This surgery was special because of its implications and huge potential,” said Dr. Shahram Majidi, the neurointerventional surgeon who performed the procedure.This was the first procedure the company has performed in the US.

The brain-computer interface (BCI) has caught the attention of many in the technological field because its device, known as the stentrode, can be inserted into the brain without cutting through a person’s skull or damaging tissue. A doctor makes an incision in the patient’s neck and feeds the stentrode via a catheter through the jugular vein into a blood vessel nestled within the motor cortex. As the catheter is removed, the stentrode, a cylindrical, hollow wire mesh opens up and begins to fuse with the outer edges of the vessel. According to Majidi, the process is very similar to implanting a coronary stent and takes only a few minutes.

A second procedure then connects the stentrode via a wire to a computing device implanted in the patient’s chest. To do this, the surgeon must create a tunnel for the wire and a pocket for the device underneath the patient’s skin much like what’s done to accommodate a pacemaker. The stentrode reads the signals when neurons fire in the brain, and the computing device amplifies those signals and sends them out to a computer or smartphone via Bluetooth.

The stentrode then uses sixteen electrodes to monitor brain activity and record the firing of neurons when a person thinks. The signal strength improves over time as the device fuses deeper into the blood vessel and gets closer to the neurons. Software is used to analyze the patterns of brain data and match them with the the user’s goal.


How to Train AI to Generate Medicines and Vaccines

Scientists have developed artificial intelligence software that can create proteins that may be useful as vaccines, cancer treatments, or even tools for pulling carbon pollution out of the air. This research was led by the University of Washington School of Medicine and Harvard University.

The proteins we find in nature are amazing molecules, but designed proteins can do so much more,” said senior author David Baker, a professor of biochemistry at UW Medicine. “In this work, we show that machine learning can be used to design proteins with a wide variety of functions.

For decades, scientists have used computers to try to engineer proteins. Some proteins, such as antibodies and synthetic binding proteins, have been adapted into medicines to combat COVID-19. Others, such as enzymes, aid in industrial manufacturing. But a single protein molecule often contains thousands of bonded atoms; even with specialized scientific software, they are difficult to study and engineer. Inspired by how machine learning algorithms can generate stories or even images from prompts, the team set out to build similar software for designing new proteins. “The idea is the same: neural networks can be trained to see patterns in data. Once trained, you can give it a prompt and see if it can generate an elegant solution. Often the results are compelling — or even beautiful,” said lead author Joseph Watson, a postdoctoral scholar at UW Medicine.

The team trained multiple neural networks using information from the Protein Data Bank, which is a public repository of hundreds of thousands of protein structures from across all kingdoms of life. The neural networks that resulted have surprised even the scientists who created them.

Deep machine learning program hallucinating new ideas for vaccine molecules

The team developed two approaches for designing proteins with new functions. The first, dubbed “hallucination” is akin to DALL-E or other generative A.I. tools that produce new output based on simple prompts. The second, dubbed “inpainting,” is analogous to the autocomplete feature found in modern search bars and email clients.

Most people can come up with new images of cats or write a paragraph from a prompt if asked, but with protein design, the human brain cannot do what computers now can,” said lead author Jue Wang, a postdoctoral scholar at UW Medicine. “Humans just cannot imagine what the solution might look like, but we have set up machines that do.

To explain how the neural networkshallucinate’ a new protein, the team compares it to how it might write a book: “You start with a random assortment of words — total gibberish. Then you impose a requirement such as that in the opening paragraph, it needs to be a dark and stormy night. Then the computer will change the words one at a time and ask itself ‘Does this make my story make more sense?’ If it does, it keeps the changes until a complete story is written,” explains Wang.

Both books and proteins can be understood as long sequences of letters. In the case of proteins, each letter corresponds to a chemical building block called an amino acid. Beginning with a random chain of amino acids, the software mutates the sequence over and over until a final sequence that encodes the desired function is generated. These final amino acid sequences encode proteins that can then be manufactured and studied in the laboratory.

The research is published in the journal Science.


One Blood Test Can Detect Over 50 Types of Cancer

Researchers are one step closer to making a multi-cancer early detection (MCED) test, that can detect over 50 types of cancer, available to select candidates: those who are age 50 and older, asymptomatic, and considered high risk for the disease. Findings from the third and final phase of the Circulating Cell-free Genome Atlas (CCGA) study have been published in the Annals of Oncology. Study findings confirm that the test is proficient in detecting and classifying cell-free DNA (cfDNA), or tumor byproducts deposited in the bloodstream of a person with cancer. The test can also identify the site of the originating tumor, even in patients with no cancer-related symptoms.

Eric A. Klein, MD, first author of the paper and Chairman Emeritus of the Glickman Urological & Kidney Institute, says these findings corroborate those of a previous CCGA sub-study, but at a larger scale and with an independent validation set. He says these results set the stage for a new cancer screening paradigm.

With the multi-cancer early detection tests, we have the opportunity to diagnose and treat cancer earlier. Used alongside other screening modalities, this could significantly reduce cancer-related deaths,” he says. For some high-mortality cancers – including liver, pancreatic and esophageal – this is the first screening test available.

Currently, only five cancer screening tests are available for patients in the United States; this includes tests for prostate, lung, breast, colorectal and cervical cancers. They each have limitations, including varying levels of invasiveness, discrepancies in use across clinical practice and high false-positive rates, which can lead to overdiagnosis and overtreatment. The promise of this new assay is raising hopes that a new paradigm is afoot. It can detect the presence of circulating cfDNA through a single blood draw and is particularly effective when it comes to identifying more lethal and later-stage cancers, believed to have more cfDNA. However, this also underscores the importance of combining the MCED with existing screening tests until further refinements are made. “Prostate cancer, for example, sheds comparatively less DNA than other tumors, making it less likely to be detected by the novel assay,” explains Dr. Klein, a urologic oncologist. GRAIL, Inc. a California-based biotech company, developed the assay and has funded international research efforts. The MCED test is now available in the United States by prescription only.


New Drug Treats Cataracts Without the Need for Surgery

A revolutionary new treatment for cataracts has shown extremely positive results in laboratory tests, giving hope that the condition, that currently can only be cured with surgery, could soon be treated with drugs.

According to the World Health Organization (WHO), 65.2 million people worldwide are living with cataracts, the leading cause of blindness and vision impairment worldwide. Cataract is a clouding of the eye lens that is caused by a disorganisation of the proteins in the lens that leads to clumps of protein forming that scatter light and severely reduce transmission to the retina. This often occurs with age, but can also be caused by the eye’s overexposure to the sun or injury, as well as smoking, medical conditions such as diabetes, and some medications. 

Surgery can correct the condition by replacing the lens with an artificial oneA team of international scientists, led by Professor Barbara Pierscionek, Deputy Dean (Research and Innovation) in the Faculty of Health, Education, Medicine and Social Care at Anglia Ruskin University (ARU), have been carrying out advanced optical tests on an oxysterol compound that had been proposed as an anti-cataract drug.

The compound oxysterol, is an oxygenated derivative of cholesterol that plays a role in the regulation and transport of cholesterolThis means that the protein organisation of the lens is being restored, resulting in the lens being better able to focus. This was supported by a reduction in lens opacity in 46% of cases.

The researchers tested an assortment of 35 wild mice and mice genetically altered to develop lens cloudiness through an alteration of their αB-crystallin or αA-crystallin proteinsIn the right eye of 26 mice, the researchers administered a single drop of an oxysterol compound, VP1-001Trusted Source, directly onto the ocular surface. Meanwhile, they gave a neutral drop of cyclodextrin in their left eyes. Nine mice were left untreated as a control group. The target of the treatment was the αA- and αB-crystallin mutations that often cause cataracts in aging.
The results have been published today in the peer-reviewed journal Investigative Ophthalmology and Visual Science.


Beams of Light Restore Hearing

A team of researchers affiliated with multiple institutions in Germany has developed a cochlear implant that converts sound waves to light signals instead of electrical signals. In their paper published in the journal Science Translational Medicine, the group describes their new hearing aid and how well it worked in test rats.

Cochlear implants work by converting  into  that are sent to nerve cells in the ear. The idea is to bypass damaged hair cells inside the cochlea to restore hearing. But because the fluid in the ear also conducts electricity, the electrical signals that are generated can cross, leading to a loss of resolution. The result is difficulty hearing in some situations, such as crowded rooms, or when listening to music with a lot of instruments. In this new effort, the researchers sought to replace the electrical signals in such devices with , which would not be muddied by the fluid in the ear, and thereby improve hearing.

In all types of cochlear devices, sound entering the ear is directed to a computer chip that processes the sound it detects. After processing, the chip directs another device to create signals that are sent to the neurons. With the new device, the researchers developed a device that would generate light using LED chips and send it through fiber cable directly to the nerve cells.

In order for such a system to work, the nerve cells inside the ear would have to be modified in some way to allow them to respond to light instead of electricity. For testing purposes, the researchers genetically modified lab rats to grow  in their  that would respond to light. In their device, they used an implant with 10 LED chips. They also trained the rats to respond to different sounds before disabling their hair cells and implanting the cochlear devices. The implants worked as hoped, as the rats were able to respond in similar ways to the same generated sounds.

The researchers suggest that in people, such a device would use 64 LED or other light source channels. They also plan to conduct more research with the device and hope to start clinical trials by 2025.


Early Stage Parkinson’s Disease Detected

The usual method of visualizing brain structure utilizes a technique most of us are familiar with, called MRI. However, it is not sensitive enough to reveal the biological changes that take place in the brain of Parkinson patients, and at present is primarily only used to eliminate other possible diagnoses.

The Hebrew University of Jerusalem (HU) researchers, led by Professor Aviv Mezer, realized that the cellular changes in Parkinson’s could possibly be revealed by adapting a related technique, known as quantitative MRI (qMRI). Their method has enabled them to look at microstructures within the part of the deep brain known as the striatum – an organ which is known to deteriorate during the progress of Parkinson’s disease. Using a novel method of analysis, developed by Mezer’s doctoral student, Elior Drori, biological changes in the cellar tissue of the striatum were clearly revealed. Moreover, they were able to demonstrate that these changes were associated with the early stages of Parkinson’s and patients’ movement dysfunction. Their findings were published 12 July 2022 in the prestigious journal Science Advances.

qMRI achieves its sensitivity by taking several MRI images using different excitation energies – rather like taking the same photograph in different colors of lighting. The HU researchers were able to use their qMRI analysis to reveal changes in the tissue structure within distinct regions of the striatum. The structural sensitivity of these measurements could only have been previously achieved in laboratories examining the brain cells of patients post mortem. Not an ideal situation for detecting early disease or monitoring the efficacy of a drug!

Description: MRI images used for automatic detection of microstructural changes in early-stage Parkinson’s Disease (PD) patients. Marked in yellow are areas in the putamen where PD patients show tissue damage, compared to healthy controls.

When you don’t have measurements, you don’t know what is normal and what is abnormal brain structure, and what is changing during the progress of the disease,” explained Mezer. The new information will facilitate early diagnosis of the disease and provide “markers” for monitoring the efficacy of future drug therapies. “What we have discovered,” he continued “is the tip of the iceberg.” It is a technique that they will now extend to investigate microstructural changes in other regions of the brain. Furthermore, the team are now developing qMRI into a tool that can be used in a clinical setting. Mezer anticipates that is about 3-5 years down the line.

Drori further suggests that this type of analysis will enable identification of subgroups within the population suffering from Parkinson’s disease – some of whom may respond differently to some drugs than others. Ultimately, he sees this analysis “leading to personalized treatment, allowing future discoveries of drug with each person receiving the most appropriate drug”.